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Microsoft AI-900 dumps VCE file - Testking AI-900 real dumps

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The Microsoft AI-900: Microsoft Azure AI Fundamentals exam is aimed at those professionals who want to demonstrate their knowledge of basic Machine Learning (ML) and Artificial Intelligence (AI) workloads. The test evaluates their understanding of how to implement both ML and AI on Azure. The candidates who pass this exam are eligible for the Microsoft Certified: Azure AI Fundamentals certification.

Certification Topics of Microsoft AI-900 Exam

Our Microsoft AI-900 exam dumps covers the following objectives of Microsoft AI-900 Exam.

Describe features of Natural Language Processing (NLP) workloads on Azure (15-20%)
Describe AI workloads and considerations (15-20%)
Describe features of conversational AI workloads on Azure (15-20%)
Describe fundamental principles of machine learning on Azure (30-35%)
Describe features of computer vision workloads on Azure (15-20%)

The Microsoft Azure AI Fundamentals certification exam consists of 40-60 questions, which must be completed within 60 minutes. The questions are presented in multiple-choice format and may include drag-and-drop, scenario-based, or knowledge-based questions. AI-900 Exam can be taken online or in-person at a certified testing center, and candidates must pay a fee to register for the exam.

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Valid AI-900 Exam Syllabus | AI-900 Questions

Microsoft AI-900 is a certification exam to test IT expertise and skills. If you find a job in the IT industry, many human resource managers in the interview will reference what Microsoft related certification you have. If you have Microsoft AI-900 Certification, apparently, it can improve your competitiveness.

Microsoft Azure AI Fundamentals Sample Questions (Q281-Q286):

NEW QUESTION # 281
To complete the sentence, select the appropriate option in the answer area.

Answer:

Explanation:
Explanation

Reference:
https://docs.microsoft.com/en-us/azure/machine-learning/concept-designer

NEW QUESTION # 282
To complete the sentence, select the appropriate option in the answer area.

Answer:

Explanation:

The correct answer is "adding and connecting modules on a visual canvas." According to the Microsoft Azure AI Fundamentals (AI-900) Official Study Guide and the Microsoft Learn module "Explore automated machine learning in Azure Machine Learning," the Azure Machine Learning designer is a drag-and-drop, no-code environment that allows users to create, train, and deploy machine learning models visually. It is specifically designed for users who prefer an intuitive graphical interface rather than writing extensive code.
Microsoft Learn defines Azure Machine Learning designer as a tool that allows you to "build, test, and deploy machine learning models by dragging and connecting pre-built modules on a visual canvas." These modules can represent data inputs, transformations, training algorithms, and evaluation processes. By linking them together, users can create an end-to-end machine learning pipeline.
The designer simplifies the machine learning workflow by allowing data scientists, analysts, and even non- developers to:
* Import and prepare datasets visually.
* Choose and connect algorithm modules (e.g., classification, regression, clustering).
* Train and evaluate models interactively.
* Publish inference pipelines as web services for prediction.
Let's analyze the other options:
* Automatically performing common data preparation tasks - This describes Automated ML (AutoML), not the Designer.
* Automatically selecting an algorithm to build the most accurate model - Also a characteristic of AutoML, where the system tests multiple algorithms automatically.
* Using a code-first notebook experience - This describes the Azure Machine Learning notebooks environment, which uses Python and SDKs, not the Designer interface.
Therefore, based on the official AI-900 learning objectives and Microsoft Learn documentation, the Azure Machine Learning designer allows you to create models by adding and connecting modules on a visual canvas, providing a no-code, interactive experience ideal for users building custom machine learning workflows visually.

NEW QUESTION # 283
Select the answer that correctly completes the sentence.

Answer:

Explanation:

The correct completion of the sentence is:
"The Form Recognizer service can be used to extract information from a driver's license to populate a database." According to the Microsoft Azure AI Fundamentals (AI-900) official study guide and the Microsoft Learn module "Identify features of computer vision workloads," Azure Form Recognizer (part of Azure AI Document Intelligence) is a document processing service that uses machine learning and optical character recognition (OCR) to extract structured data, key-value pairs, and text from documents such as invoices, receipts, identity cards, and driver's licenses.
This service allows businesses to automate data entry and document processing workflows by converting physical or scanned documents into machine-readable formats. For example, with a driver's license, Form Recognizer can extract structured data fields such as Name, Date of Birth, License Number, and Expiration Date, and automatically populate those values into a database or CRM system.
The AI-900 study materials emphasize that Form Recognizer is designed to handle both structured and unstructured document layouts. It includes prebuilt models for common document types (like invoices, receipts, and identity documents) and supports custom models for domain-specific forms.
By comparison:
* Computer Vision extracts general text or image content but doesn't structure or label extracted fields.
* Custom Vision is used for training image classification or object detection models.
* Conversational Language Understanding is for processing text or speech to determine intent, not extracting document data.
Therefore, based on the Microsoft Learn AI-900 official study content, the Form Recognizer service is the correct choice, as it is explicitly designed to extract and structure data from documents like driver's licenses, forms, and receipts - making it ideal for automatically populating a database.

NEW QUESTION # 284
To complete the sentence, select the appropriate option in the answer area.

Answer:

Explanation:

NEW QUESTION # 285
You are developing a model to predict events by using classification.
You have a confusion matrix for the model scored on test data as shown in the following exhibit.

Use the drop-down menus to select the answer choice that completes each statement based on the information presented in the graphic.
NOTE: Each correct selection is worth one point.

Answer:

Explanation:

Explanation:
Box 1: 11

TP = True Positive.
The class labels in the training set can take on only two possible values, which we usually refer to as positive or negative. The positive and negative instances that a classifier predicts correctly are called true positives (TP) and true negatives (TN), respectively. Similarly, the incorrectly classified instances are called false positives (FP) and false negatives (FN).
Box 2: 1,033
FN = False Negative
Reference:
https://docs.microsoft.com/en-us/azure/machine-learning/studio/evaluate-model-performance

NEW QUESTION # 286
......

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